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• Exploiting New Patterns of Genome Damage in Triple Negative Breast Cancer

  Genomic instability, a feature of triple negative breast cancers (TNBC), represents an opportunity for discovery of biologic and clinically relevant subgroups of patients. Owing to TP53 mutation in the majority of cases, DNA repair deficiency through loss of BRCA1 and BRCA2, and by expression features patterning a basal cell of origin, TNBC represents a molecularly and clinically distinct group of breast cancer patients. Unfortunately, targetable molecular features of TNBC remain elusive and TNBC patients suffer the poorest outcomes amongst clinical subgroups. Within TNBC patients, responses to treatment vary and although gene expression patterns within TNBC have been identified, little progress has been made in developing biomarkers; effective stratification as a route to directing patients to more targeted therapy is lacking. In this study, we exploit mutational processes in TNBC as a new opportunity to stratify patients and to understand the evolutionary progression of TNBC cells harboring specific DNA repair properties.

  Study phs003038

• Single molecule molecular inversion probe capture developed using the CIViC database

  This study evaluated the use of the Clinical Interpretations of Variants in Cancer database (CIViC) to develop an Open-sourced CIViC Annotation Pipeline (OpenCAP). OpenCAP is a resource that allows users to develop a clinical capture panel that can be linked back to clinical summaries within the CIViC database. This method for capture panel development and variant annotation was tested using 27 cancer samples from 5 tumor subtypes with original exome or genome sequencing. Specifically, using OpenCAP, 111 variants were identified as relevant for the capture panel and 2,027 smMIPs were designed to target these variants. The smMIPs panel design was employed on all samples to validate the capture panel design. When compared to original sequencing, the CIViC smMIPs capture panel demonstrated a 95% sensitivity for variant detection (n = 61 variants). Additionally, the CIViC smMIPs capture panel identified 182 additional clinically relevant variants that had been missed on original sequencing.

  Study phs001890

• University of Miami Udall Center of Excellence Identification of Rare Variants in PD through Whole Exome Sequencing

  The focus of this study is to identify a new level of genetic variation, i.e. rare genetic variants with a population frequency less than 5%, usually less than 1%, which are believed to provide a stronger risk per variant than those studied to date in the large genome wide association studies (GWAS). To do this we are generating whole exome sequencing data on the Illumina HiSeq. Each HiSeq produces at least 600 billion base pairs of DNA sequence in one run. Whole exome sequencing sequence data, about 50 million base pairs, or about 1.5% of the total DNA of each person's genome, is generated. We are using this data to look for new DNA variations that give risk for Parkinson disease, as well as "modifiers", that may lead to having more severe or milder disease or later or earlier ages of onset.

  Study phs000908

• Multimodal Analysis for Human Ex Vivo Studies Shows Extensive Molecular Changes from Delays in Blood Processing

  Multi-omic profiling of human peripheral blood is increasingly utilized to identify biomarkers and pathophysiologic mechanisms of disease. The importance of these platforms in clinical and translational studies led us to investigate the impact of delayed blood processing on the numbers and state of peripheral blood mononuclear cells (PBMC) and on the plasma proteome. Similar to previous studies, we show minimal effects of delayed processing on the numbers and general phenotype of PBMCs up to 18 hours. In contrast, profound changes in the single-cell transcriptome and composition of the plasma proteome become evident as early as 6 hours after blood draw. These reflect patterns of cellular activation across diverse cell types that lead to progressive distancing of the gene expression state and plasma proteome from native in vivo biology. Differences accumulating during an overnight rest (18 hours) could confound relevant biologic variance related to many underlying disease states.

  Study phs002280

• High-Throughput LINE-1 Retrotransposon Discovery in Humans

  The aim of this study is to discover LINE-1 (L1) insertion sites present in humans that are absent from the reference genome sequence. We use the distinguishing nucleotide characteristics of human-specific L1 elements to resequence the L1 3' flanking regions thus locating the L1 insertion sites whether or not they are present in the reference genome assembly. In doing so, we have uncovered a higher than expected number of non-reference L1 insertions, an average of 152 insertions per individual. In addition, we find that any two individuals differ at an average of 285 sites with respect to presence or absence of L1 insertions in those sites, and use this to estimate the rate of retrotransposition in humans at 1 event per 140 live births (95% c.i. 1/95 to 1/270). We show that individual 'L1 profiles' recapitulate genetic ancestry as expected, and find that dimorphic insertions are more frequent in introns relative to fixed insertions.

  Study phs000273

• A Whole Genome Association Scan for Myopia and Glaucoma Endophenotypes using Twin Studies

  Myopia and glaucoma are highly prevalent ophthalmic disorders worldwide and contribute significantly to ocular morbidity. There is substantial evidence that genetic factors play a significant role in the development of non-syndromic myopia and glaucoma. We propose to perform mapping studies for well-characterized twin populations in the United Kingdom and Australia in order to ultimately identify implicated genes for these disorders and related ocular parameters. This will provide a fundamental molecular understanding of how these disorders develop, and may lead to directed physiologic (i.e. pharmacologic, gene therapy) interventions. Our aim is to dissect the genetic basis of the eye disorders myopia and glaucoma. Instead of limited analyses of the trait/disease in a dichotomous manner, we are using continuous phenotypes of measures of refraction and intermediate phenotypes of glaucoma to analyze quantitative traits in unselected population samples of volunteer twins. Achievement of this goal requires cooperative efforts and large sample sizes. Thus, we have created an international collaboration of large complementary studies.

  Study phs000142

• Uncovering Gene Regulatory Differences between Human and Chimpanzee Neural Cells

  A major challenge in human evolutionary biology is to pinpoint the genetic differences that underlie phenotypic changes in the human lineage, such as increased neuron number and a prolonged period of neuronal maturation. Here, we used human-chimpanzee tetraploid cells to distinguish changes in gene expression due to cis-acting sequence variants that change local gene regulation, from trans expression changes due to species differences in the cellular environment, in neural progenitor cells and excitatory neurons using RNA-seq and ATAC-seq. Using a CRISPR inhibition screen with scRNA-seq, transcription factor motif analyses with CUT&Tag, and downstream single-locus studies with RNA-seq, we further characterized cis-acting gene regulatory differences, including changes to FOS, TNIK, FOSL2, and MAZ, that influence neurogenesis and neuronal maturation. This study identifies specific genomic changes that may contribute to human neural specializations and provides a general framework for understanding genetic differences that underlie human traits.

  Study phs004053

• Geographical structure and differential natural selection among North European populations

  European populations and epidemiological cohorts are of special significance in the current era of genomic research aiming to characterize the background of common human diseases. The genome sequence, detailed information of genetic variations between individuals, high-throughput molecular technologies and novel statistical strategies create new possibilities to define genetic and life-style risk factors behind common health problems. Studies of large population cohorts are needed to transform the genetic information to detailed understanding of the predisposing factors in diseases affecting most human populations. European twin cohorts provide a unique competitive advantage for investigations of the role of genetics and environment or life style in the etiology of common diseases. This project will apply and develop new molecular and statistical strategies to analyze unique European twin and other population cohorts to define and characterise the genetic, environmental and life-style components in the background of health problems like obesity, migraine, coronary heart disease and stroke, representing major health care problems worldwide.

  Study EGAS00000000033

• MutWP6__CRUK_Grand_Challenge_Mutographs_of_Cancer__Botseq

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Within Mutographs, work lead by the Sanger Institute will investigate whether detection of somatic mutations and mutational signatures in circulating white blood cells can be developed into a practical, generic system for surveying and monitoring multiple different endogenous and exogenous exposures, providing an ‘observatory’ on somatic mutational processes in humans. Whole genome sequences are generated at the Wellcome Sanger Institute (Illumina HiSeqX). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001004330

• MutWP6__CRUK_Grand_Challenge_Mutographs_of_Cancer__alkylating_agents

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Within Mutographs, work lead by the Sanger Institute will investigate whether detection of somatic mutations and mutational signatures in circulating white blood cells can be developed into a practical, generic system for surveying and monitoring multiple different endogenous and exogenous exposures, providing an ‘observatory’ on somatic mutational processes in humans. Whole genome sequences are generated at the Wellcome Sanger Institute (Illumina HiSeqX). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003637

• MutWP6__CRUK_Grand_Challenge_Mutographs_of_Cancer__oncology_agents

  he Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Within Mutographs, work lead by the Sanger Institute will investigate whether detection of somatic mutations and mutational signatures in circulating white blood cells can be developed into a practical, generic system for surveying and monitoring multiple different endogenous and exogenous exposures, providing an ‘observatory’ on somatic mutational processes in humans. Whole genome sequences are generated at the Wellcome Sanger Institute (Illumina HiSeqX). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001004125

• Distribution of ctDNA levels in plasma of early-stage non-small cell lung cancer patients measured using personalised ctDNA analysis

  Blood-based assays have shown increasing ability to detect circulating tumour DNA (ctDNA) in patients with early-stage cancer. However, detection of ctDNA in patients with non-small cell lung cancer (NSCLC) has continued to prove challenging. We performed retrospective analysis to quantify ctDNA levels in a cohort of 100 patients with early-stage NSCLC prior to treatment with curative intent. Where tumour tissue was available for whole exome sequencing, mutations identified were used to define patient-specific sequencing assays. For those 90 patients, plasma cell-free DNA was sequenced to high depth across capture panels targeting a median of 328 mutations specific to each patient. Data was analysed using Integration of Variant Reads (INVAR), detecting ctDNA in 66.7% of patients, including 52.7% (29 of 55) patients with stage I disease and >88% detection for patients with stage II and III disease (16/18 and 15/17). ctDNA was detected in plasma at fractional concentrations as low as 9.1x10-6, and in patients with tumour volumes as low as 0.23 cm3. A 36-gene sequencing panel (InVisionFirst-LungTM) was used to analyse plasma DNA in 27 samples including the 10 cases without tumour exome data, and detected ctDNA in 59% of samples tested (16 of 27). Across the entire cohort, detection rates were higher in squamous cell carcinoma patients compared to adenocarcinoma patients (81% vs. 59%). Detection of ctDNA prior to treatment was associated with significantly shorter time free from relapse, across all patients and in patient subgroups, with Hazard Ratios ranging from 2.25 to >11. Our analysis indicates that for patients with stage I NSCLC, the median ctDNA fraction in plasma is approx. 12 parts per million (0.0012%). This indicates the limits of detection that would be required for ctDNA-based liquid biopsies to detect ctDNA in the majority of patients with early-stage NSCLC.

  Dataset EGAD00001006230

• Single cell RNA sequencing and Whole Genome Sequencing on different cells from the same sample for a triple negative patient derived xenograft and ovarian cancer cell lines.

  Measuring gene expression of genomically defined tumour clones at single cell resolution would associate functional consequences to somatic alterations, as a prelude to elucidating pathways driving cell population growth, resistance and relapse. In the absence of scalable methods to simultaneously assay DNA and RNA from the same single cell, independent sampling of cell populations for parallel measurement of single cell DNA and single cell RNA must be computationally mapped for genome-transcriptome association. Here we present clonealign, a robust statistical framework to assign gene expression states to cancer clones using single-cell RNA-seq and DNA-seq independently sampled from an heterogeneous cancer cell population. We apply clonealign to triple-negative breast cancer patient derived xenografts and high-grade serous ovarian cancer cell lines and discover clone-specific dysregulated biological pathways not visible using either DNA-Seq or RNA-Seq alone.

  Study EGAS00001003387

• Next_gen_seq_of_eye_cancers

  Retinoblastoma (RB), the commonest eye cancer in children was the first cancer for which a genetic cause was identified: the Rb1 gene is a tumour suppressor gene that is mutated in RB. The Rb1 gene defect alone does not predict the clinical outcome. We propose to study other possible mechanisms: 1. Stepwise further mutations occur in RB, increasing its carcinogenesis. We will sequence the whole genome in RB tissue, and relate the different genes expressed to the treatments used. 2. Extracellular matric proteins contribute to a tumour permissive environment for RB to continue to grow. This includes Samll Leucine Rich Proteoglycans (SLRP), a family of 15 secreted extracellular matrix proteins involved in eye development. 3. Cancer stem cells (CSC), a subpopulation of treatment resistant cells, drive RB tumours, and whether these stem cells can be manipulated for new therapies. The aim of this study is to assist finding targeted diagnostic techniques and treatments for RB.

  Study EGAS00001002309

• Trans-ethnic genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation

  We carried out a trans-ethnic genome-wide association and replication study of blood pressure phenotypes amongst up to 320,251 individuals of East Asian, European and South Asian ancestry. We find genetic variants at 12 novel loci to be associated with blood pressure (P=3.9x10-11 to P=5.0x10-21). The sentinel blood pressure SNPs are enriched for association with DNA methylation at multiple nearby CpG sites, suggesting that at some of the loci identified DNA methylation may lie on the regulatory pathway linking sequence variation to blood pressure. The sentinel SNPs at the 12 novel loci point to genes involved in vascular smooth muscle (IGFBP3, KCNK3, PDE3A and PRDM6) and renal (ARHGAP24, OSR1, SLC22A7, TBX2) function. The novel and known genetic variants predict increased left ventricular mass, circulating levels of NT-proBNP, cardiovascular and all-cause mortality (P=0.04 to 8.6x10-6). Our results provide new evidence for the role of DNA methylation in blood pressure regulation.

  Study EGAS00001001427

• Single_Cell_RNAseq_at_various_stages_of_HiPSCs_differentiating_toward_definitive_endoderm_and_endoderm_derived_lineages

  When comparing the differentiation capacities of pluripotent stem cell lines that have different genetic backgrounds, batch to batch experimental variablility poses a significant challenge, especially when trying to identify smaller effects. One way to address this issue is to differentiate several different lines in the same culture dish, thereby elimating experimental variation. In addition, it allows researchers to analyze many more lines with less experiments. Parallel single cell RNA-Seq exploits that individual cells are tagged and hence each cell can be reliably assigned to the donor of origin based on the genetic variants it contains. In addition, analyzing the genetic signature of single cells within a differentiating population can reveal differentation stages that are not easily detected in bulk RNAseq data. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002278

• COVID19 Host Genetic Initiative

  The COVID-19 host genetics initiative is a bottom-up collaborative effort that has three main goals: 1. Provide an environment to foster the sharing of resources to facilitate COVID-19 host genetics research (e.g. protocols, questionnaires). 2. Organize analytical activities across studies to identify genetic determinants of COVID-19 susceptibility and severity. 3. Provide a platform to share the results from such activities, as well as the individual-level data where possible, to benefit the broader scientific community. Here, we release the harmonized individual-level data for the subset of individuals who participated in COVID-19 HGI. Please refer to this data dictionary: https://docs.google.com/spreadsheets/d/1whu_MjShXxbdoAJMCYxZ5C-vWOcRivwfWglTcBRNZgQ/edit#gid=470747846 Please cite both Nakanishi, T el al. J Clin Invest 2021 (PMID: 34597274) and COVID-19 Host Genetics Initiative, Nature 2021 (PMID: 34237774) when you use these data for your publications.

  Study EGAS00001005304

• Colorectal adenomas, NKI-AvL TGO series Stool-Proteomics

  Colorectal cancer (CRC) develops from normal epithelium, through a benign precursor lesion called adenoma, by accumulation of genetic alterations affecting oncogenes and tumour suppressor genes. About 5% of colorectal adenomas are estimated to progress to CRC. However, it is important to identify which adenomas actually are at high-risk of progression, because these should serve as intermediate endpoints for e.g. CRC screening programs. In clinical practice, adenomas with a size of ≥10 mm, villous component and/or high-grade dysplasia, called advanced adenomas, are considered high-risk, although this classification lacks solid evidence. Specific DNA copy number changes are associated with adenoma-to-carcinoma progression.For this tissue dataset, we applied low-pass whole genome sequencing to 98 non-advanced and advanced adenomas. These adenomas were classified as lesions with low-risk or high-risk of progression, according to the presence of specific DNA copy number changes (Carvalho et al, CancerPrevRes, 2018).

  Study EGAS00001002953

• Methylome sequencing of cell-free DNA and RRBS of solid tissue

  Early cancer detection by cell-free DNA (cfDNA) faces multiple challenges: low fraction of tumor cfDNA, molecular heterogeneity of cancer, and sample sizes not sufficient to reflect diverse patient population. We develop a cancer detection approach to address these challenges. It consists of an assay, cfMethyl-Seq, for cost-effective sequencing of cfDNA methylome (with >12-fold enrichment over whole genome bisulfite sequencing in CpG islands), and a computational method to extract methylation information and diagnose patients. Applying our system to 408 colon, liver, lung, and stomach cancer patients and controls, at 97.9% specificity we achieve 80.7% and 74.5% sensitivity in detecting all-stage and early-stage cancer, and 89.1% and 85.0% accuracy for locating tissue-of-origin of all-stage and early-stage cancer, respectively. Our approach cost-effectively retains methylome profiles of cancer abnormalities, thereby permitting the classification models to learn new features as training cohorts grow, and expanding their scope to other cancer types.

  Study EGAS00001006020

• Spatial and temporal transcriptomics of medulloblastoma with chromothripsis identifies multiple genetic clones that resist to treatment and lead to relapse

  From all paediatric brain tumours, medulloblastomas with chromothripsis, a form of genome instability leading to massive genome rearrangements, are particularly aggressive. To dissect the complex biology underlying the aggressiveness of chromothriptic medulloblastomas, we applied spatial transcriptomics to i) chromothriptic and non-chromothriptic medulloblastomas from the same molecular subgroup (n=13) and ii) patient-derived xenografts from chromothriptic medulloblastoma, from the minimal residual disease stage to regrown tumours (n=11). Chromothriptic medulloblastomas showed higher spatial intra-tumour heterogeneity, proliferation and stemness, but lower immune infiltration and differentiation, as compared with non-chromothriptic medulloblastomas. Spatial mapping of genetic clones identified phenotypic features such as degree of differentiation, proliferation and immune infiltration enriched in specific clones. Cells from multiple genetic clones resisted treatment and gave rise to relapse in patient-derived xenografts of chromothriptic medulloblastoma. We identified a potential role of tumour microtubes in treatment resistance in chromothriptic medulloblastoma.

  Study EGAS00001007128

• INCLUDE: The Epidemiology of Transient Leukemia in Newborns with Down Syndrome

  The INCLUDE (INvestigation of Co-occurring conditions across the Lifespan to Understand Down syndromE) Project is an NIH-wide collaboration that seeks to improve health and quality-of-life for people with Down syndrome. The INCLUDE Project Data Coordinating Center and partners created the INCLUDE Data Hub, a centralized data resource that allows access to large-scale clinical and multi-omics datasets specific to Down syndrome and supports collaborative, cloud-based analysis to accelerate scientific discoveries related to Down syndrome and its co-occurring conditions.Down syndrome (DS) is associated with a remarkably high risk of childhood acute myeloid leukemia (AML), with an approximately 500-fold increased risk of the rare subtype acute megakaryoblastic leukemia. Though largely treatable, a proportion of myeloid leukemia in DS (ML-DS) patients relapse with dismal survival. ML-DS is preceded by a preleukemia, transient abnormal myelopoiesis (TAM), which presents clinically at birth and is driven by somatic truncating mutations in the erythro-megakaryocytic transcription factor gene GATA1. Up to 15% of DS newborns have TAM, and this can be fatal in up to 20% of cases. A further 10-15% of newborns with DS harbor subclonal GATA1 mutations with clinically silent disease (i.e., Silent TAM). Of the DS newborns with either TAM or Silent TAM (i.e., transient leukemia), up to 15% will acquire additional somatic mutations and progress to ML-DS. We predict that germline variation modifies the risk of developing somatic truncating GATA1 mutations, the first step towards ML-DS, however this has yet to be examined. To address this, the main aim of this X01 study is to perform the first genetic association study of GATA1 mutations in DS, through whole-genome sequencing (WGS) of 470 DS newborns in the Oxford Down Syndrome Cohort Study (ODSCS). Targeted sequencing of GATA1 has already been performed in the 470 DS newborns in the ODSCS, with 130 (28%) confirmed to harbor a somatic truncating GATA1 mutation. We will perform a genome-wide association study (GWAS) of GATA1 mutations to assess genetic variation genome-wide, in particular focusing on variants in candidate genes on the trisomic chromosome 21, RUNX1, ERG, ETS2, and DYRK1A, which have previously been associated with upregulation of GATA1. We will also carry out a chromosome X-wide association study (XWAS) to investigate genetic variation at the GATA1 gene, which resides on chromosome X. WGS data will also enable us to assess the potential role of copy number variation in the risk of transient leukemia in DS. Discovering genetic risk factors for GATA1 mutations in DS may reveal targets for new targeted therapies for TAM, and also inform the etiology of ML-DS as well as AML in the non-DS population. Finally, the ODSCS includes rich phenotypic data for the 470 DS newborns, including clinical diagnosis of TAM and other hematologic complications, complete blood counts, maternal pregnancy complications, and information on congenital heart disease and other birth defects. Thus, whole genome sequencing data in DS newborns from the ODSCS will provide a rich resource for the DS research community.

  Study phs002982

• Loss of SDHB promotes dysregulated iron homeostasis, oxidative stress and sensitivity to ascorbate

  Succinate dehydrogenase is a key enzyme in the tricarboxylic acid cycle and the electron transport chain. All four subunits of succinate dehydrogenase are tumor suppressor genes predisposing to paraganglioma, but only mutations in the SDHB subunit are associated with increased risk of metastasis. Here we generated an Sdhd knockout chromaffin cell line and compared it to Sdhb-deficient cells. Both cell types exhibited similar SDH loss of function, metabolic adaptation, and succinate accumulation. In contrast, Sdhb-/- cells showed hallmarks of mesenchymal transition associated with increased DNA hypermethylation and a stronger pseudo-hypoxic phenotype compared to Sdhd-/- cells. Loss of SDHB specifically led to increased oxidative stress associated with dysregulated iron and copper homeostasis in the absence of NRF2 activation. High-dose ascorbate exacerbated the increase in mitochondrial reactive oxygen species, leading to cell death in Sdhb-/- cells. These data establish a mechanism linking oxidative stress to iron homeostasis that specifically occurs in SDHB deficient cells and may promote metastasis. They also highlight high-dose ascorbate as a promising therapeutic strategy for SDHB-related cancers.

  Study EGAS00001005279

• Host factors dictate gut microbiome alterations in chronic kidney disease more strongly than to kidney function

  Despite recent progress, microbial markers in Chronic Kidney Disease (CKD) remain inconclusive. We combined quantitative faecal metagenomics (N=130 CKD cohort) and cross-study biomarker comparisons (Ntotal=4420) to study microbiome associations with glomerular filtration rate (eGFR; kidney function) and 4-year CKD progression. Transit time (TT) and medications primarily explained microbiome variation, trumping eGFR-related effects. Metagenome analysis showed increased p-cresol and indole synthesis potential and decreased plant-to-animal CAZyme ratios with lower eGFR, coupled to a Bact1 to Rum enterotype shift, suggesting saccharolytic-to-proteolytic microbiome transitions linked to dietary guidelines and slowed-down TT. Peritoneal dialysis patients showed increased (dysbiotic) Bact2 prevalence and linked intestinal inflammation. Only Escherichia coli, an unnamed Alistipes species and Bifidobacterium adolescentis were confounder-independent markers for eGFR, but these nor previous markers convincingly replicated across 11 studies. No predictors for CKD progression were found. Together, poor evidence for microbiome biomarkers but substantial eGFR-independent effects were found, suggesting potential for nutritional and TT interventions in CKD.

  Study EGAS50000000646

• Dynamics of Tumor Heterogeneity from Primary to Metastatic Dissemination in Prostate Cancer

  PRO-SPeCT: PROstate cancer heterogeneity deconvolution through Single cell Profiling of Chromatin accessibility and Transcriptomic output Identifying drivers of cancer progression to guide treatment selection is hindered by limited abilities to understand tumor heterogeneity’s impact on evolution. Here, we delineated the phenotypic variability across ~300,000 prostate tumor cells collected from multiple loci in primary and matched locoregional metastases. We found inter-patient heterogeneity to be confined to malignant populations. While malignant cell populations exhibit intra-locus heterogeneity, they maintain inter-loci phenotypic similarity within a patient’s prostate gland. In addition, the intra-locus heterogeneity between malignant cell populations is paired with a common clonal architecture. Lastly, we show that malignant cell populations disseminating to locoregional lymph nodes mirror the clonal architecture and phenotypic heterogeneity observed across primary tumor loci while showcasing cell state transition toward inflammatory phenotypes. These findings provide insights into distinct measures of tumor heterogeneity, revealing diverse evolutionary paths across patients converging to common phenotypic adaptations in early prostate cancer progression.

  Study EGAS50000000524

• Spatial predictors of response to immunotherapy in microsatellite stable metastatic colorectal cancer

  Microsatellite stable (MSS) colorectal cancers (CRC) are largely unresponsive to immune checkpoint inhibition (ICI), prompting investigation into strategies to enhance sensitivity. The MAYA trial, which utilized temozolomide (TMZ) in MGMT-silenced MSS mCRC, hypothesized that TMZ-induced hypermutation could sensitize tumors to ICI. This phase II trial met its primary endpoint, demonstrating durable clinical responses with TMZ combined with ipilimumab and nivolumab. To elucidate factors influencing response heterogeneity, we conducted multi-omic spatial profiling of samples from patients who participated in the MAYA trial, including baseline and on-treatment tissue and blood specimens. While increased neoantigen load following TMZ exposure did not consistently predict for deep responses, spatial profiling revealed key determinants. Lymphocyte proportions, particularly CD8+KI67+ cells, within stromal and tumor compartments, along with macrophage composition (CD68+CD163+ cells) at the tumor-stromal interface, were predictive of response. Treatment pressures dynamically altered the tumor microenvironment composition and activated peripheral immune cells. This study is the first to identify spatial predictors of response to this promising novel treatment approach for MSS CRC.

  Study EGAS50000001567